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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: xlm-roberta-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: xlm-roberta-base-hin-finetuned
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # xlm-roberta-base-hin-finetuned
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+
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+ This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1860
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+ - F1: 0.7535
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+ - Roc Auc: 0.8671
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+ - Accuracy: 0.74
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.4196 | 1.0 | 109 | 0.3772 | 0.0 | 0.5 | 0.31 |
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+ | 0.3586 | 2.0 | 218 | 0.2947 | 0.1149 | 0.5683 | 0.39 |
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+ | 0.2381 | 3.0 | 327 | 0.2153 | 0.5976 | 0.7550 | 0.65 |
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+ | 0.1881 | 4.0 | 436 | 0.1626 | 0.7613 | 0.8478 | 0.76 |
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+ | 0.1228 | 5.0 | 545 | 0.1616 | 0.7681 | 0.8682 | 0.75 |
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+ | 0.1085 | 6.0 | 654 | 0.1794 | 0.7227 | 0.8415 | 0.71 |
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+ | 0.0865 | 7.0 | 763 | 0.1545 | 0.7622 | 0.8640 | 0.77 |
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+ | 0.0747 | 8.0 | 872 | 0.1624 | 0.7701 | 0.8739 | 0.74 |
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+ | 0.0561 | 9.0 | 981 | 0.1982 | 0.7479 | 0.8578 | 0.73 |
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+ | 0.0432 | 10.0 | 1090 | 0.1725 | 0.7579 | 0.8643 | 0.74 |
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+ | 0.0418 | 11.0 | 1199 | 0.1910 | 0.7533 | 0.8689 | 0.72 |
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+ | 0.0327 | 12.0 | 1308 | 0.1860 | 0.7535 | 0.8671 | 0.74 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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